Assessment and Monitoring of Soil Degradation during Land Use Change Using Multivariate Analysis

Abstract

Not only are soil erosion and overall loss of soil fertility serious issues for loess‐derived soils of developing nations, such as Iran, but they are also global problems. This research investigated the role of land use change and its effect on soil degradation in cultivated, pasture, and urban lands, when compared with native forest in terms of declining of soil quality and fertility. Multivariate statistical methods including principal component analysis and cluster analysis were employed to determine the relative magnitude of anthropogenic and natural influences on soil quality. Partial least squares (PLS), principal component regression, and ordinary least squares regression were used to predict soil cation exchange capacity using soil characteristics. Principal component analysis identified five primary components of soil quality. PC1 explained 41·01% of the total variance, PC2 accounted for 15·29%, and PC3 accounted for 11·3%. PC4 and PC5 accounted for 7·37% and 4·19% of the total variance, respectively. Cluster analysis revealed that the lowest soil quality occurred in urban soils. An exponential semivariogram using PLS predictions revealed stronger spatial dependence among cation exchange capacity [r2 = 0·80, root mean square error (RMSE) = 1·99] than the other methods, principal component regression [r2 = 0·84, RMSE = 2·45] and ordinary least squares [r2 = 0·84, RMSE = 2·45]. Therefore, the PLS method provided the best model for the data. In stepwise regression analysis, mean weight diameter and labile carbon were selected as influential variables in all soils. This study quantified reductions in numerous soil quality parameters resulting from extensive land‐use changes and urbanization in the Ziarat watershed in northern Iran. Copyright © 2016 John Wiley & Sons, Ltd.

Assessment of the Spatiotemporal Effects of Land Use Changes on Runoff and Nitrate Loads in the Talar River

“…Recent studies claim that land use changes are one of the most important factors that affect surface water characteristics and soil fertility [6][7][8]. During the last decades, land use changes and water quality of rainwater harvesting systems have been associated with population growth, urban development, intensive agricultural activities, degradation of pastures and deforestation [9,10].…”

Modeling soil cation exchange capacity in multiple countries

“…Determining soil quality requires identification of soil properties that are important in a soil's ability to carry out its various functions as well as being responsive to changes in land use and land management (Paz-Ferreiro and Fu, 2016;Zolfaghari et al, 2016). CEC plays an important role in soil quality (Brevik, 2009;Khaledian et al, 2016a;Taghizadeh-Mehrjardi, 2016). CEC can be influenced by soil physical (e.g., soil texture), chemical (e.g., pH, mineralogy), and biological (e.g., soil organic matter) characteristics (Mukherjee and Zimmerman, 2013); therefore, CEC integrates aspects of all three of the indicator groups commonly used to determine soil quality (Brevik, 2009) and there are strong positive relationships between CEC and the soil colloidal fraction (Kweon et al, 2013).…”

Islands of biogeodiversity in arid lands on a polygons map study: Detecting scale invariance patterns from natural resources maps

“…This situation makes it very important to make the best possible use of all information that is available to us, particularly when it involves little additional expense. This has led to the increasing use of proximal and remote sensing, advanced statistical methods, and pedotransfer functions within soil science in recent years (Brevik et al, 2016a,b;Khaledian et al, 2016;Reidy et al, 2016). This study, along with past studies that have looked at the relationships between soil and geology maps (Brevik and Miller, 2015), show that there is no reason that we should not also utilize maps of related natural resources (geology, hydrology, vegetation, etc.…”